Eliminating execution of jobs-based operational costs of related reports

ABSTRACT

Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

PRIORITY

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 15/246,577, filed on Aug. 25, 2016, entitled“ELIMINATING EXECUTION OF JOBS-BASED OPERATIONAL COSTS OF RELATEDREPORTS”; which is a continuation of Ser. No. 15/062,712 filed Mar. 7,2016 and issued as U.S. Pat. No. 9,483,309B2 on Nov. 1, 2016 entitled“ELIMINATING EXECUTION OF JOBS-BASED OPERATIONAL COSTS OF RELATEDREPORTS; which is a continuation of U.S. patent application Ser. No.14/088,501, filed on Nov. 25, 2013 and issued as U.S. Pat. No.9,336,504B2 on May 10, 2016 entitled “ELIMINATING EXECUTION OFJOBS-BASED OPERATIONAL COSTS OF RELATED REPORTS; the entire contents ofwhich are incorporated herein by reference.

BACKGROUND

The disclosed subject matter relates generally to optimizing executionof jobs in a computing environment and, more particularly, tostrategically eliminating jobs according to the costs for generatingreports associated with the jobs.

Many enterprises rely on business intelligence (BI) reports forday-to-day decision making. BI reports are generated by way of extract,transform, and load (ETL) jobs, which require computing resources (e.g.,CPU, memory, etc.) to run. Thus, each ETL job has an operational costthat can be calculated based on the cost of processing resourcesallocated to that job.

In general, the number of jobs proportionally grows with the number ofBI reports generated. If sufficient capacity and proper planning are notpresent, the computing resources may become overloaded and fail toproperly support the jobs. It is desirable to maintain sufficientcapacity to support the important jobs, while culling the less importantjobs or reports to lower operational costs.

Typically, a human operator examines each report to see if the reportmeets certain cost-benefit criteria based on which the report and thesupporting jobs may be decommissioned. This process is a manual task andexpensive. Further, the process typically does not result in substantialsavings, due to lack of insight about operational costs of individualreports.

SUMMARY

In accordance with embodiments, methods, systems and computer programproducts for optimizing operational costs in a computing environment areprovided. A method includes identifying high-cost jobs that are executedto generate one or more reports in the computing environment,identifying one or more reports the generation of which is dependent onthe execution of the high-cost jobs, and culling at least a first jobfrom among the high-cost jobs, in response to determining that a benefitachieved from the reports that depend on the first job does not justifycosts associated with generating the reports.

A system comprising one or more logic units is provided. The one or morelogic units are configured to perform the functions and operationsassociated with the above-disclosed methods. In yet another embodiment,a computer program product comprising a computer readable storage mediumhaving a computer readable program is provided. The computer readableprogram when executed on a computer causes the computer to perform thefunctions and operations associated with the above-disclosed methods.

One or more of the above-disclosed embodiments in addition to certainalternatives are provided in further detail below with reference to theattached figures. The disclosed subject matter is not, however, limitedto any particular embodiment disclosed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The disclosed embodiments may be better understood by referring to thefigures in the attached drawings, as provided below.

FIG. 1 illustrates an exemplary computing environment in accordance withone or more embodiments, wherein a data warehouse and a data mart areimplemented to aggregate data for the production of BI reports.

FIG. 2 is a flow diagram of an exemplary method for reducing the costsassociated with the generation of reports in accordance with oneembodiment.

FIGS. 3 and 4 are block diagrams of hardware and software environmentsin which the disclosed systems and methods may operate, in accordancewith one or more embodiments.

Features, elements, and aspects that are referenced by the same numeralsin different figures represent the same, equivalent, or similarfeatures, elements, or aspects, in accordance with one or moreembodiments.

DETAILED DESCRIPTION

A portion of this disclosure may contain material, which is subject tocopyright protection. The owner has no objection to the facsimilereproduction by any one of the patent document or the patent disclosure,as it appears in the Patent and Trademark Office patent file or records,but otherwise reserves all copyrights whatsoever.

Certain marks referenced herein may be common law or registeredtrademarks of the applicant, the assignee or third parties affiliated orunaffiliated with the applicant or the assignee. Use of these marks isfor providing an enabling disclosure by way of example and shall not beconstrued to exclusively limit the scope of the disclosed subject matterto material associated with such marks.

In the following, numerous specific details are set forth to provide athorough description of various embodiments. Certain embodiments may bepracticed without these specific details or with some variations indetail. In some instances, certain features are described in less detailso as not to obscure other aspects. The level of detail associated witheach of the elements or features should not be construed to qualify thenovelty or importance of one feature over the others.

Referring to FIG. 1, in the exemplary operating environment 100, one ormore server systems 190 may be utilized to process day-to-daytransactions in a business enterprise, or other computing environments.Server systems 190 may provide relevant data to a data warehouse 110 byway of scheduling and executing computer implemented jobs. An ETL toolmay be used to move selected data to domain-specific data marts 120 tofacilitate reporting, analysis and decision making in the operationalenvironment 100.

Cubes 150 may be utilized for the purpose of filtering or aggregatingdata from a data warehouse 110 or a data mart 120 to support theefficient generation of reports 170. For example, a cube 150 may beimplemented to filter out information included in a data mart 120 ordata warehouse 110 to facilitate the generation of a report 170 thatincludes sales information for a product on a quarterly basis, where thetiming data stored in the data warehouse 110 or the data mart 120 mayprovide the sales data on a daily or weekly basis, for example.

Data in data marts 120 or cubes 150 may be processed by way of one ormore BI tools (e.g., IBM Cognos Enterprise®) to generate one or morereports 170. To maintain an efficient reporting process, a three-stageapproach may be implemented in accordance with one embodiment. In afirst stage, high-cost jobs that are scheduled for execution to generateone or more reports 170 are identified. The cost of a job may bedetermined based on processor usage at a certain time interval (e.g.,during peak hours). Once the high-cost jobs are identified, in a secondstage, reports associated with those jobs are identified. In a thirdstage, certain jobs are selected for elimination to the extent that thereports depending on the selected jobs do not justify the costassociated with those jobs.

In eliminating the unwanted reports, in one embodiment, theinterdependencies between multiple jobs and reports are taken intoconsideration so that, for example, if one job contributes to more thanone report, a job associated with a low value report is not eliminatedif that job is also needed for a high value report. As provided infurther detail below, reports may be grouped together as a function ofthe set of common reports that are dependent on a job, such thataggregated cost savings may be achieved by removing a group of reportsthat depend on a common set of jobs.

To determine the operational costs associated with a job, in oneembodiment, the number of CPUs deployed to run the job is considered.This is because each additional CPU deployed may incur hardware costsand software licensing costs associated with the corresponding database,application server and ETL engine that are utilized to facilitate jobexecution. In one implementation, since the number of CPUs deployedincreases during a peak usage window, narrowing the peak usage windowhelps reduce the number of CPUs required to run the jobs and thereforethe operational costs.

Referring to FIG. 2, in one embodiment, usage metrics for a jobexecution environment may be determined by identifying the peak CPUusage time range (S210), identifying the jobs running during that timerange (S220), and identifying the CPU usage or usage contribution factorfor a job (S230). Once the above metrics are calculated, the job costsby CPU usage may be calculated (S240). Below, a detailed example process(e.g., algorithm) is provided that facilitates the translation of CPUusage metrics to a more meaningful measure to indicate the associatedjob costs.

In one implementation, a data lineage tool may be used to identify thedependency of a report on one or more jobs and determine the cost foreach report (S250, S260). In this manner, the reports that contribute topeak CPU usage (which contribute disproportionately to the operationalcosts) may be detected. These reports may be the proper candidates forculling. Thus, in one implementation, the benefits (e.g., business need,importance, etc.) of a candidate report is examined and weighed againstthe report's cost (S270) by way of a cost-benefit analysis, for example.The jobs or the dependent reports that do not meet a certain criteriaare eliminated (S280).

In one example scenario, InfoSphere Information Server that includes aDataStage ETL engine may be used to schedule and run the jobs in an ETLenvironment. In this example, a DataStage operational console may beused to provide CPU metrics for each job run. A metadata asset managermy be utilized for integration with Cognos BI reports that includesMetadata Workbench which deduces a data lineage graph from the DataStagejobs to the Cognos BI reports. Without limitation, the followingexemplary process may be implemented in one embodiment:

a) The DataStage Operational Console may be used to:

-   -   Identify the peak CPU usage time range.    -   Identify the DataStage jobs running during that time range.    -   For a job, find its CPU usage and determine the individual cost        of the job based on its CPU usage.        b) Using Metadata Workbench invoke a data lineage tool for a job        to identify the downstream BI reports that are using the job        data either directly or indirectly.        c) Determine the individual cost of a report based on the costs        of the jobs which provide the report's data.        d) Determine the cost for a report based the analysis above        calculated metrics and eliminate the reports whose business        needs do not justify their cost together with the jobs that        provide their data.

Employing the above process to cull jobs and reports will reduce thepeak CPU usage. The above process may be repeated iteratively toidentify eliminate additional jobs and reports until a thresholdcondition is reached. For the purpose of providing a clarifying detailedexample, in the following, a specific exemplary implementation isintroduced. It is noteworthy, however, that the specific features orscenarios provided are not to be construed to limit the scope of theclaimed subject matter to such limitations.

In one example implementation, the unit of report cost may not berepresented as currency, but rather as a comparison to one anotherreport in terms of relative CPU usage. For example, if there are 5reports that are being compared, it may be adequate to provideinformation that indicates: report_X uses 40% of the resources while theother reports use 15% of the resources each. In this example, report_Xis the most expensive and therefore would be the first candidate for thecost-benefit analysis and elimination. That is, if measuring thereport's business value against its cost does not make sense, thenreport_X and jobs on which that report depends may be eliminated,provided that those jobs are not needed for generating the otherreports.

Job costs may be calculated based on a DataStage operational consoleindication of the percentage of CPU usage for a job that is run during apeak window. This percentage indicates the cost number that isassociated with the job. Jobs that do not run during the peak window donot impact the peak usage if culled. Therefore, in one implementationcost associated with such jobs may be considered zero. Once the jobcosts are determined, then the cost associated with the correspondingreports may be calculated.

By way of example, consider a scenario where there are two reports (R1,R2) and three jobs (J1, J2, J3) running during the peak usage windowsuch that:

-   -   J1 moves data that is needed for R1. The cost of J1 is 5.    -   J2 moves data that is needed for R2. The cost of J2 is 6.    -   J3 moves data that is needed for R1 and R2. The cost of J3 is 9.

In the above example, if R1 is deemed unnecessary and removed then J1can be removed since it is providing data only to R1. However, J2 and J3cannot be removed, since J2 and J3 are providing data also to R2. Assuch, removing R1 will save running J1 and therefore will save the costof 5.

On the other hand, in the above example, if R2 is deemed unnecessary andremoved, then J2 may be removed, since it is providing data only to R2.J1 and J3 may not be removed, since J1 and J3 are providing data also toR1. As such, removing R2 will save running J2 and therefore will savethe cost of 6

In a different scenario, if R1 and R2 are both deemed unnecessary andremoved then J1, J2 and J3 may all be removed since they are providingdata only to R1 and R2. As such, removing R1 and R2 will save the costof 5+6+9, which is 20.

As provided in the above example scenarios, the cost savings achieved byremoving two reports is more than the aggregate savings achieved byremoving each report independently. As shown above, J3 could be removedand its cost saved if both R1 and R2 were removed.

In accordance with one implementation, to determine the operational costof a report, it may be important to distinguish between the cost savingsachieved by removing an individual report vs. the cost savings achievedby removing a collection of reports, where such collection of reportsrepresents the full set of reports that are dependent on a single set ofjobs.

In other words, the individual cost of a report may be determined by thecost saved by removing only the report. In one implementation, datalineage results may be used to find the jobs contributing data to aparticular report. In one example implementation, the related operatingcosts for a job may be assigned according to the following, for example:

-   -   If the job is not executing during the highest peak of CPU        usage, then its individual cost is zero.    -   If the job is executing during the highest peak of CPU usage but        is needed by other reports too, then its individual cost is        zero.    -   If the job is executing during the highest peak of CPU usage and        is needed only by a particular report, then the job cost is        added to the reports individual cost.

Based on the above, the cost of a report may be calculated as theaggregate cost of all jobs that contribute to the report and thecollective cost of a “report group” may be determined as the cost savedby removing a group of reports. As noted earlier, data lineage resultsmay be used to determine the jobs contributing data to a group ofreports. For a job the associated costs with that job may be assignedbased on the following, for example:

-   -   If the job is not executing during the highest peak of CPU usage        then its cost is zero.    -   If the job is executing during the highest peak of CPU usage but        it is needed by reports not in this group then its cost is zero.    -   If the job is executing during the highest peak of CPU usage and        it is needed by only this report group then its cost is added to        the report group's cost.

In one implementation, the cost of the report group is the aggregatecost of jobs that contribute to the report group. In the following,another detailed example is provided, without limitation, to help betterunderstand the methodology discussed above.

Non-limiting Example:

Reviewing a DataStage CPU utilization graph for an ETL operationalenvironment may indicate peak usage on the 21st of Nov between 01:00 amand 03:30 am. The jobs that were executing during this peak may be thejobs that have the highest real cost. Removing these jobs real savingsmay be achieved. In this example, an operation console may be accessedto find the jobs that were running on the 21st of Nov between 01:00 amand 03:30 am. For example, the operation console may indicate that a job“loadDW EMEA” was executing during the peak and the related CPU usagewas 15%. Further investigation may further indicate that there were fourjobs executing during the peak usage window and the job costs are 8, 12,9 and 15, for example.

A data lineage tool may be used for the target jobs and the reports thatdepend on the target jobs may be found. For example, the data lineagetool may provide the following lineage summary:

-   -   The job “loadDW EMEA” is feeding only R1 its cost is 15.    -   The job J1 is feeding reports R2 and R3 its cost is 12.    -   The job J2 is feeding reports R1, R2 and R3 its cost is 9.    -   The job J3 is feeding reports R1, R2 and R3 its cost is 8.

Consider a scenario with a single job that costs 15 and contributes totwo different reports: R1 and R2. We would like to determine how doesthe job costs are attributed to R1 separately, because it is not fair orcorrect to say that R1 cost is 15, since the cost 15 is also needed forR2. To resolve this issue, the following costs are considered:

-   -   R1 individual cost is 0    -   R2 individual cost is 0    -   R1 and R2 collective cost is 15

Based upon the lineage summary and the calculated job costs, the reportscosts may be determined as follows:

Individual costs:

-   -   R1=15—The job “loadDW EMEA” is only required for R1 and the cost        of this job is 15. No other jobs running during the peak        contribute solely to this report    -   R2=0—The jobs (J1, J2, J3) running during the CPU peak that        contribute to this report also contribute to other reports    -   R3=0—The jobs (J1, J2, J3) running during the CPU peak that        contribute to this report also contribute to other reports

Collective costs:

-   -   The cost of collection (R2, R3) is 12—Job J1 is executing during        the peak CPU usage and contributes solely to these reports, the        cost of J1 is 12 and therefore the cost of this collection is 12    -   The cost of collection (R1, R2, R3) is 44—Jobs J1, J2, J3 and        “loadDW EMEA” are executing during the peak CPU usage and        contribute solely to these reports, their costs are 12, 9, 8, 15        respectively and therefore the cost of this collection is 44

Based on the above, a human operator or a computer implemented systemmay be able to understand that culling individual reports R2 or R3 willnot result in costs saving. However, the following actions may providesubstantial cost savings:

-   -   Cull R1 and save 15    -   Cull R2 and R3 and save 12    -   Cull R1, R2 and R3 and save 44

As shown, culling R1 and the corresponding dependent jobs is moreimpactful than culling both R2 and R3 and all their dependent jobs.According to the above implantations, the individual and collectivecosts of one or more jobs and the reports that depend on such jobs maybe calculated, so that the jobs and reports that do not meet a costbenefit analysis may be properly eliminated.

Advantageously, using the above methodology, costs associated withadding additional hardware or software licensing for different systemcomponents may be avoided or reduced. Further, the need for hiringadditional human operators, and human-related errors or shortcomings inremoving non-impactful reports due to lack of insight into theoperational cost of each report may be also eliminated.

References in this specification to “an embodiment”, “one embodiment”,“one or more embodiments” or the like, mean that the particular element,feature, structure or characteristic being described is included in atleast one embodiment of the disclosed subject matter. Occurrences ofsuch phrases in this specification should not be particularly construedas referring to the same embodiment, nor should such phrases beinterpreted as referring to embodiments that are mutually exclusive withrespect to the discussed features or elements.

In different embodiments, the claimed subject matter may be implementedas a combination of both hardware and software elements, oralternatively either entirely in the form of hardware or entirely in theform of software. Further, computing systems and program softwaredisclosed herein may comprise a controlled computing environment thatmay be presented in terms of hardware components or logic code executedto perform methods and processes that achieve the results contemplatedherein. The methods and processes, when performed by a general purposecomputing system or machine, convert the general purpose machine to aspecific purpose machine.

Referring to FIGS. 3 and 4, a computing system environment in accordancewith an exemplary embodiment may be composed of a hardware environment1110 and a software environment 1120. The hardware environment 1110 maycomprise logic units, circuits or other machinery and equipments thatprovide an execution environment for the components of softwareenvironment 1120. In turn, the software environment 1120 may provide theexecution instructions, including the underlying operational settingsand configurations, for the various components of hardware environment1110.

Referring to FIG. 3, the application software and logic code disclosedherein may be implemented in the form of machine readable code executedover one or more computing systems represented by the exemplary hardwareenvironment 1110. As illustrated, hardware environment 110 may comprisea processor 1101 coupled to one or more storage elements by way of asystem bus 1100. The storage elements, for example, may comprise localmemory 1102, storage media 1106, cache memory 1104 or othermachine-usable or computer readable media. Within the context of thisdisclosure, a machine usable or computer readable storage medium mayinclude any recordable article that may be utilized to contain, store,communicate, propagate or transport program code.

A computer readable storage medium may be an electronic, magnetic,optical, electromagnetic, infrared, or semiconductor medium, system,apparatus or device. The computer readable storage medium may also beimplemented in a propagation medium, without limitation, to the extentthat such implementation is deemed statutory subject matter. Examples ofa computer readable storage medium may include a semiconductor orsolid-state memory, magnetic tape, a removable computer diskette, arandom access memory (RAM), a read-only memory (ROM), a rigid magneticdisk, an optical disk, or a carrier wave, where appropriate. Currentexamples of optical disks include compact disk, read only memory(CD-ROM), compact disk read/write (CD-R/W), digital video disk (DVD),high definition video disk (HD-DVD) or Blue-ray™ disk.

In one embodiment, processor 1101 loads executable code from storagemedia 1106 to local memory 1102. Cache memory 1104 optimizes processingtime by providing temporary storage that helps reduce the number oftimes code is loaded for execution. One or more user interface devices1105 (e.g., keyboard, pointing device, etc.) and a display screen 1107may be coupled to the other elements in the hardware environment 1110either directly or through an intervening I/O controller 1103, forexample. A communication interface unit 1108, such as a network adapter,may be provided to enable the hardware environment 1110 to communicatewith local or remotely located computing systems, printers and storagedevices via intervening private or public networks (e.g., the Internet).Wired or wireless modems and Ethernet cards are a few of the exemplarytypes of network adapters.

It is noteworthy that hardware environment 1110, in certainimplementations, may not include some or all the above components, ormay comprise additional components to provide supplemental functionalityor utility. Depending on the contemplated use and configuration,hardware environment 1110 may be a machine such as a desktop or a laptopcomputer, or other computing device optionally embodied in an embeddedsystem such as a set-top box, a personal digital assistant (PDA), apersonal media player, a mobile communication unit (e.g., a wirelessphone), or other similar hardware platforms that have informationprocessing or data storage capabilities.

In some embodiments, communication interface 1108 acts as a datacommunication port to provide means of communication with one or morecomputing systems by sending and receiving digital, electrical,electromagnetic or optical signals that carry analog or digital datastreams representing various types of information, including programcode. The communication may be established by way of a local or a remotenetwork, or alternatively by way of transmission over the air or othermedium, including without limitation propagation over a carrier wave.

As provided here, the disclosed software elements that are executed onthe illustrated hardware elements are defined according to logical orfunctional relationships that are exemplary in nature. It should benoted, however, that the respective methods that are implemented by wayof the exemplary software elements may be also encoded in the hardwareelements by way of configured and programmed processors, applicationspecific integrated circuits (ASICs), field programmable gate arrays(FPGAs) and digital signal processors (DSPs), for example.

Referring to FIG. 4, software environment 1120 may be generally dividedinto two classes comprising system software 1121 and applicationsoftware 1122 as executed on one or more hardware environments 1110. Inone embodiment, the methods and processes disclosed here may beimplemented as system software 1121, application software 1122, or acombination thereof. System software 1121 may comprise control programs,such as an operating system (OS) or an information management system,that instruct one or more processors 1101 (e.g., microcontrollers) inthe hardware environment 1110 on how to function and processinformation. Application software 1122 may comprise but is not limitedto program code, data structures, firmware, resident software, microcodeor any other form of information or routine that may be read, analyzedor executed by a processor 1101.

In other words, application software 1122 may be implemented as programcode embedded in a computer program product in form of a machine-usableor computer readable storage medium that provides program code for useby, or in connection with, a machine, a computer or any instructionexecution system. Moreover, application software 1122 may comprise oneor more computer programs that are executed on top of system software1121 after being loaded from storage media 1106 into local memory 1102.In a client-server architecture, application software 1122 may compriseclient software and server software. For example, in one embodiment,client software may be executed on a client computing system that isdistinct and separable from a server computing system on which serversoftware is executed.

Software environment 1120 may also comprise browser software 1126 foraccessing data available over local or remote computing networks.Further, software environment 1120 may comprise a user interface 1124(e.g., a graphical user interface (GUI)) for receiving user commands anddata. It is worthy to repeat that the hardware and softwarearchitectures and environments described above are for purposes ofexample. As such, one or more embodiments may be implemented over anytype of system architecture, functional or logical platform orprocessing environment.

It should also be understood that the logic code, programs, modules,processes, methods and the order in which the respective processes ofeach method are performed are purely exemplary. Depending onimplementation, the processes or any underlying sub-processes andmethods may be performed in any order or concurrently, unless indicatedotherwise in the present disclosure. Further, unless stated otherwisewith specificity, the definition of logic code within the context ofthis disclosure is not related or limited to any particular programminglanguage, and may comprise one or more modules that may be executed onone or more processors in distributed, non-distributed, single ormultiprocessing environments.

As will be appreciated by one skilled in the art, a software embodimentmay include firmware, resident software, micro-code, etc. Certaincomponents including software or hardware or combining software andhardware aspects may generally be referred to herein as a “circuit,”“module” or “system.” Furthermore, the subject matter disclosed may beimplemented as a computer program product embodied in one or morecomputer readable storage medium(s) having computer readable programcode embodied thereon. Any combination of one or more computer readablestorage medium(s) may be utilized. The computer readable storage mediummay be a computer readable signal medium or a computer readable storagemedium. A computer readable storage medium may be, for example, but notlimited to, an electronic, magnetic, optical, electromagnetic, infrared,or semiconductor system, apparatus, or device, or any suitablecombination of the foregoing.

In the context of this document, a computer readable storage medium maybe any tangible medium that can contain, or store a program for use byor in connection with an instruction execution system, apparatus, ordevice. A computer readable signal medium may include a propagated datasignal with computer readable program code embodied therein, forexample, in baseband or as part of a carrier wave. Such a propagatedsignal may take any of a variety of forms, including, but not limitedto, electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable storage medium may betransmitted using any appropriate medium, including but not limited towireless, wireline, optical fiber cable, RF, etc., or any suitablecombination of the foregoing. Computer program code for carrying out thedisclosed operations may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages.

The program code may execute entirely on the user's computer, partly onthe user's computer, as a stand-alone software package, partly on theuser's computer and partly on a remote computer or entirely on theremote computer or server. In the latter scenario, the remote computermay be connected to the user's computer through any type of network,including a local area network (LAN) or a wide area network (WAN), orthe connection may be made to an external computer (for example, throughthe Internet using an Internet Service Provider).

Certain embodiments are disclosed with reference to flowchartillustrations or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments. It will beunderstood that each block of the flowchart illustrations or blockdiagrams, and combinations of blocks in the flowchart illustrationsand/or block diagrams, can be implemented by computer programinstructions. These computer program instructions may be provided to aprocessor of a general purpose computer, a special purpose machinery, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions or acts specified in the flowchart or blockdiagram block or blocks.

These computer program instructions may also be stored in a computerreadable storage medium that can direct a computer, other programmabledata processing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablestorage medium produce an article of manufacture including instructionswhich implement the function or act specified in the flowchart or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computer or machineimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions or acts specified in the flowchart or blockdiagram block or blocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical functions. It should also be noted that, in somealternative implementations, the functions noted in the block may occurin any order or out of the order noted in the figures.

For example, two blocks shown in succession may, in fact, be executedsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams or flowchartillustration, and combinations of blocks in the block diagrams orflowchart illustration, may be implemented by special purposehardware-based systems that perform the specified functions or acts, orcombinations of special purpose hardware and computer instructions.

The claimed subject matter has been provided here with reference to oneor more features or embodiments. Those skilled in the art will recognizeand appreciate that, despite of the detailed nature of the exemplaryembodiments provided here, changes and modifications may be applied tothe embodiments without limiting or departing from the generallyintended scope. These and various other adaptations and combinations ofthe embodiments provided here are within the scope of the disclosedsubject matter as defined by the claims and their full set ofequivalents.

What is claimed is:
 1. A computer program product comprising anon-transitory computer readable storage medium having a computerreadable program, wherein the computer readable program when executed ona computer causes the computer to: identify high-cost jobs from among aplurality of jobs that are executed by one or more computing devices inthe computing environment to generate one or more reports in thecomputing environment, the high-cost jobs determined as a function ofresource usage of resources in the computing environment, wherein theresource usage comprises at least one of CPU usage, data storage usage,memory usage, and network bandwidth usage; identify one or more reportsthe generation of which is dependent on the execution of the high-costjobs; and cull at least a first job from among the high-cost jobs, inresponse to determining that a benefit achieved from the reports thatdepend on the first job does not justify costs associated withgenerating the reports, wherein costs associated with a report arecalculated based on aggregated cost of jobs on which the report depends,and wherein the cost of the individual job is determined by: a) if thejob is not executing during the highest peak of resource usage, then itsindividual cost is zero; b) if the job is executing during the highestpeak of resource usage but is needed by other reports too, then itsindividual cost is zero; and c) if the job is executing during thehighest peak of resource usage and is only needed by a particularreport, then the job cost is added to the report's individual job cost.